Mobile robots are increasingly being suggested as solutions to various problems on their own, thanks to the significant progress in the field of mobile robotics in recent years. In recent years, advancements in computer vision hardware and algorithms have...
Artificial intelligence depends on large and often high-dimensional datasets, creating privacy risks that are not fully addressed by conventional policy statements. Public agencies and infrastructure operators may process health records, mobility traces,...
The integration of data analytics in Offender Management Systems (OMS) has revolutionized risk assessment, predictive analysis, and offender classification, fundamentally transforming criminal justice decision-making. Traditional methods, reliant on...
As organizations increasingly leverage Artificial Intelligence (AI) to foster innovation and improve operational performance, the availability of high-quality, well-documented, and easily accessible data has become a decisive factor for success. This paper...
In recent years, Machine Learning (ML) has advanced from the undertaking of not many PC fans abusing the chance of PCs figuring out how to mess around. A piece of Mathematics (Statistics) that only here and there thought about computational methodologies,...
Growth Potential at the Crossroads of Artificial Intelligence, Robotics, and Synthetic Biology. Biomedical and bioengineering advancements are impeded by our incapacity to foretell how biological systems will act. We are unable to extrapolate behaviour on a...
The oil and gas industry operate within a highly complex and volatile supply chain environment, demanding efficient management practices to ensure operational reliability and cost-effectiveness. Traditional Enterprise Resource Planning (ERP) systems, while...
While there is a lot of written about AI's great potential, no studies have looked at how well it improves patient safety during robot-assisted surgery (RAS). In accordance with the PRISMA 2020 declaration, a literature search was carried out using PubMed,...
The integration of artificial intelligence into healthcare systems presents multifaceted technical and pedagogical challenges that require comprehensive multidisciplinary approaches. This article examines the practical obstacles encountered in AI...
Disaster recovery is a critical aspect of healthcare information technology, ensuring the continuity of patient care and data integrity in the face of cyber threats, natural disasters, and system failures. The integration of hybrid cloud solutions has...
Governments worldwide face increasing challenges in responding to disasters and crises, necessitating resilient IT strategies that ensure continuity, adaptability, and efficiency. A robust IT framework for disaster response and crisis management integrates...
The swift advancement of Artificial Intelligence (AI) has necessitated the generation of novel opportunities and efficiency across several sectors. Simultaneously, the dependence on AI for personal data throughout its training process encompasses several...
The WEKA (Waikato Environment for Knowledge Analysis) provides a comprehensive suite of tools and functionalities for applying data mining techniques to large and complex datasets. Designed to support both academic research and industrial applications, WEKA...
Ensemble machine-learning models have achieved striking published results for financial transaction fraud detection, with recent peer-reviewed studies reporting F1-scores as high as 0.99 and accuracy exceeding 99.9 percent on benchmark credit-card fraud...
In the rapidly evolving landscape of cloud computing, the integration of Artificial Intelligence (AI) has become essential for enhancing data-driven decision-making and improving operational efficiency. However, ensuring data reliability in AI-powered cloud...
Recognition of images and voices, processing of natural languages, and even healthcare are just a few areas that have benefited greatly from the advent of machine learning and deep learning. Machine learning and deep learning are discussed in this article...
The intersection of artificial intelligence, genetic information, and health research presents complex ethical dilemmas that challenge existing data protection frameworks, including the European General Data Protection Regulation. This article examines the...
Artificial intelligence governance often fails at the point where broad principles must be converted into decisions about controls, approvals, monitoring, and evidence. A single checklist cannot govern every system because the consequences of AI vary...
Data governance has become a pivotal element in assessing the efficacy and enduring stability of IT systems in the contemporary data-centric landscape. It includes frameworks that assist organizations in overseeing data collection, storage, processing,...
Governments worldwide recognize the increasing threats posed by cyberattacks on critical infrastructure, which encompasses sectors such as energy, healthcare, finance, and transportation. To mitigate risks and enhance resilience, national cybersecurity...
The use of artificial intelligence in critical infrastructure creates a new class of cyber-physical and institutional risks. AI systems depend on extensive data pipelines, complex models, software supply chains, cloud services, interfaces, and continuous...
Public-sector artificial intelligence can shape access to services, inspections, benefits, taxation, healthcare, mobility, and other consequential decisions. Its legitimacy therefore depends on more than predictive performance. Systems must avoid...
In the current digital landscape, characterized by the rapid expansion of Artificial Intelligence and data-intensive technologies, data governance has evolved into a strategic foundation for sustainable organizational growth rather than a purely regulatory...
Through a data utilisation value chain, AI/Data commons will promote the construction of an open collaborative ecosystem based on PCI (Participation- Collaboration-Incentives). This will be accomplished by preserving data sovereignty and protecting...
The rapid expansion of web-based platforms, digital services, and data-driven applications has significantly increased the complexity of governing online ecosystems. AI-Enabled Policy-Driven Web Governance represents an advanced governance paradigm that...
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